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Record W2137847742 · doi:10.1002/app.28106

Anomalous moisture diffusion in an epoxy adhesive detected by magnetic resonance imaging

2008· article· en· W2137847742 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueJournal of Applied Polymer Science · 2008
Typearticle
Languageen
FieldEngineering
TopicUltrasonics and Acoustic Wave Propagation
Canadian institutionsUniversity of New BrunswickUniversity of WaterlooWestern UniversityUniversité de Moncton
Fundersnot available
KeywordsMoistureMaterials scienceDiffusionAbsorption (acoustics)AdhesiveFick's laws of diffusionEpoxyDeuteriumAnalytical Chemistry (journal)Nuclear magnetic resonanceComposite materialChemistryThermodynamicsPhysicsChromatographyAtomic physics

Abstract

fetched live from OpenAlex

Abstract Non‐Fickian or anomalous diffusion is frequently observed when the absorption of moisture by a polymer is being studied. Different models have been presented in the literature that can accurately predict the trends of the weight‐gain curves. However, it is not always clear which of these models yield good predictions of moisture distribution. This article presents a time‐resolved moisture distribution study of an epoxy sample immersed in deuterated water (D 2 O) at 70°C over a period of 2.5 months. The moisture distribution was measured during that period with a novel high‐resolution magnetic resonance imaging technique that is well adapted to the imaging of thin plates. The experimental results showed that the concentration of D 2 O at the surface of the sample increased with time, even after 2.5 months. These results were used to evaluate the performance of several standard diffusion models. Although this study is phenomenological, it appears that a model featuring time‐varying boundary conditions yields the best representation of moisture absorption for these samples. © 2008 Wiley Periodicals, Inc. J Appl Polym Sci, 2008

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.201
Threshold uncertainty score0.419

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.004
GPT teacher head0.188
Teacher spread0.184 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it